Beyond approximate factorization, we have also performed exact factorization with the sIM. As mention in Section , we consider the integer factorization problem as a benchmark to compare the performance of our sIM implementation against other probabilistic solvers or D-Wave's quantum annealers. We found that the sIM can factor random semiprimes up to 32-bits reliably (Supplementary Information, Fig. REF ). To the best of our knowledge, this result is by far the best among all other approaches of solving factorization as an optimization problem, for example by D-Wave and others [1]}, [2]}, [3]}, [4]}, [5]}, [6]}. Table REF  presents a comparison of integer factorization across the state-of-the-art hardware platforms, and the sIM reports the largest factorization up to 32-bit. What is common to all these solvers is they express factorization as a frustrated spin-glass problem in which the ground state is searched using classical or quantum annealing.
